4 citations · 7 across the 6 of their papers we have counts for
4 papers · 1 filter
Block-structured Operator Inference for coupled multiphysics model reduction
Benjamin G. Zastrow, Anirban Chaudhuri, Karen E. Willcox +2
This paper presents a block-structured formulation of Operator Inference as a way to learn structured reduced-order models for multiphysics systems. The approach specifies the gove…
Projection-based multifidelity linear regression for data-scarce applications
Vignesh Sella, Julie Pham, Karen Willcox +1
Surrogate modeling for systems with high-dimensional quantities of interest remains challenging, particularly when training data are costly to acquire. This work develops multifide…
TumorTwin: A python framework for patient-specific digital twins in oncology
Michael Kapteyn, Anirban Chaudhuri, Ernesto A. B. F. Lima +5
Background: Advances in the theory and methods of computational oncology have enabled accurate characterization and prediction of tumor growth and treatment response on a patient-s…
Validating the predictions of mathematical models describing tumor growth and treatment response
Guillermo Lorenzo, David A. Hormuth, Chengyue Wu +7
Despite advances in methods to interrogate tumor biology, the observational and population-based approach of classical cancer research and clinical oncology does not enable anticip…